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Article: Single-ensemble-based eigen-processing methods for color flow imaging-Part I. the Hankel-SVD filter

TitleSingle-ensemble-based eigen-processing methods for color flow imaging-Part I. the Hankel-SVD filter
Authors
Issue Date2008
PublisherIEEE.
Citation
Ieee Transactions On Ultrasonics, Ferroelectrics, And Frequency Control, 2008, v. 55 n. 3, p. 559-572 How to Cite?
AbstractBecause of their adaptability to the slow-time signal contents, eigen-based filters have shown potential in improving the flow detection performance of color flow images. This paper proposes a new eigen-based filter called the Hankel-SVD filter that is intended to process each slow- time ensemble individually. The new filter is derived using the notion of principal Hankel component analysis, and it achieves clutter suppression by retaining only the principal components whose order is greater than the clutter eigen- space dimension estimated from a frequency-based analysis algorithm. To assess its efficacy, the Hankel-SVD filter was first applied to synthetic slow-time data (ensemble size: 10) simulated from two different sets of flow parameters that model: (1) arterial imaging (blood velocity: 0 to 38.5 cm/s, tissue motion: up to 2 mm/s, transmit frequency: 5 MHz, pulse repetition period: 0.4 ms) and 2) deep vessel imaging (blood velocity: 0 to 19.2 cm/s, tissue motion: up to 2 cm/s, transmit frequency: 2 MHz, pulse repetition period: 2.0 ms). In the simulation analysis, the post-filter clutter- to-blood signal ratio (CBR) was computed as a function of blood velocity. Results show that for the same effective stopband size (50 Hz), the Hankel-SVD filter has a narrower transition region in the post-filter CBR curve than that of another type of adaptive filter called the clutter- downmixing filter. The practical efficacy of the proposed filter was tested by application to in vivo color flow data obtained from the human carotid arteries (transmit frequency: 4 MHz, pulse repetition period: 0.333 ms, ensemble size: 10). The resulting power images show that the Hankel-SVD filter can better distinguish between blood and moving- tissue regions (about 9 dB separation in power) than the clutter-downmixing filter and a fixed-rank multi-ensemble- based eigen-filter (which showed a 2 to 3 dB separation). © 2006 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/57455
ISSN
2015 Impact Factor: 2.287
2015 SCImago Journal Rankings: 0.910
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorYu, ACHen_HK
dc.contributor.authorCobbold, RSCen_HK
dc.date.accessioned2010-04-12T01:37:12Z-
dc.date.available2010-04-12T01:37:12Z-
dc.date.issued2008en_HK
dc.identifier.citationIeee Transactions On Ultrasonics, Ferroelectrics, And Frequency Control, 2008, v. 55 n. 3, p. 559-572en_HK
dc.identifier.issn0885-3010en_HK
dc.identifier.urihttp://hdl.handle.net/10722/57455-
dc.description.abstractBecause of their adaptability to the slow-time signal contents, eigen-based filters have shown potential in improving the flow detection performance of color flow images. This paper proposes a new eigen-based filter called the Hankel-SVD filter that is intended to process each slow- time ensemble individually. The new filter is derived using the notion of principal Hankel component analysis, and it achieves clutter suppression by retaining only the principal components whose order is greater than the clutter eigen- space dimension estimated from a frequency-based analysis algorithm. To assess its efficacy, the Hankel-SVD filter was first applied to synthetic slow-time data (ensemble size: 10) simulated from two different sets of flow parameters that model: (1) arterial imaging (blood velocity: 0 to 38.5 cm/s, tissue motion: up to 2 mm/s, transmit frequency: 5 MHz, pulse repetition period: 0.4 ms) and 2) deep vessel imaging (blood velocity: 0 to 19.2 cm/s, tissue motion: up to 2 cm/s, transmit frequency: 2 MHz, pulse repetition period: 2.0 ms). In the simulation analysis, the post-filter clutter- to-blood signal ratio (CBR) was computed as a function of blood velocity. Results show that for the same effective stopband size (50 Hz), the Hankel-SVD filter has a narrower transition region in the post-filter CBR curve than that of another type of adaptive filter called the clutter- downmixing filter. The practical efficacy of the proposed filter was tested by application to in vivo color flow data obtained from the human carotid arteries (transmit frequency: 4 MHz, pulse repetition period: 0.333 ms, ensemble size: 10). The resulting power images show that the Hankel-SVD filter can better distinguish between blood and moving- tissue regions (about 9 dB separation in power) than the clutter-downmixing filter and a fixed-rank multi-ensemble- based eigen-filter (which showed a 2 to 3 dB separation). © 2006 IEEE.en_HK
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofIEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Controlen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rights©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.subject.meshAlgorithmsen_HK
dc.subject.meshBlood Flow Velocity - physiologyen_HK
dc.subject.meshCoronary Circulation - physiologyen_HK
dc.subject.meshCoronary Vessels - ultrasonographyen_HK
dc.subject.meshEchocardiography, Doppler, Color - instrumentation - methodsen_HK
dc.titleSingle-ensemble-based eigen-processing methods for color flow imaging-Part I. the Hankel-SVD filteren_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0885-3010&volume=55&issue=3&spage=559&epage=572&date=2008&atitle=Single-ensemble-based+eigen-processing+methods+for+color+flow+imaging—Part+I.+The+Hankel-SVD+filteren_HK
dc.identifier.emailYu, ACH:alfred.yu@hku.hken_HK
dc.identifier.authorityYu, ACH=rp00657en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.doi10.1109/TUFFC.2008.682en_HK
dc.identifier.pmid18407847-
dc.identifier.scopuseid_2-s2.0-44849100646en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-44849100646&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume55en_HK
dc.identifier.issue3en_HK
dc.identifier.spage559en_HK
dc.identifier.epage572en_HK
dc.identifier.isiWOS:000254118500004-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridYu, ACH=8699317700en_HK
dc.identifier.scopusauthoridCobbold, RSC=7005052711en_HK

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